Optimisation (#127)
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@ -161,6 +161,10 @@ and then only convert them to C data structures when you have to call the C func
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3. The raylib.* functions are potentially 1.5x faster than the pyray.* equivalents, so if you need a tiny bit more performance
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you can switch your inner loop functions to these.
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4. There is a version of Python that is faster than Pypy: GraalPy. However it's not fully compatible with all Python
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packages. It doesn't work with CFFI and so doesn't work with this binding. But it *is* compatible with the
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*Java* binding, Jaylib! There is an example of this here: https://github.com/electronstudio/megabunny/tree/master/raylib-python-jaylib
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## Bunnymark
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@ -175,6 +179,8 @@ you can switch your inner loop functions to these.
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| Raylib Python CFFI 3.7 | Python 3.9 Nuitka | 8600 | 5.1% |
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| Raylib Python CFFI 3.7 Dynamic | Python 3.9 | 6300 | 3.7% |
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See also https://github.com/electronstudio/megabunny/
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# Packaging your app
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You can create a standalone binary using the Nuitka compiler. For example, here is how to package Bunnymark:
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